In order to understand the validity and relative performance of different text classification methods for identifying the moral concerns manifested in the MFRC, we report baseline results for a number of NLP approaches: Distributed Dictionary Representations [1]}, Bidirectional Encoder Representations from Transformers [2]}, and Multi-Label [3]} BERT models. These baselines can both be used as evidence about the relative performance of various NLP models on the task of moral concern detection and also inform future methodological work including to help calibrate new models of moral sentiment classification.
